ORIGINAL RESEARCH article
Front. Immunol.
Sec. Viral Immunology
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1576414
This article is part of the Research TopicViral Surface Spikes: Host Cell Entry, Immune Responses and Evasion, and Implications for Viral Infection, Inhibition and ReboundView all articles
Evolving fitness and immune escape: A retrospective analysis of SARS-CoV-2 spike protein (2020-2024) using protein language model
Provisionally accepted
- University of Georgia, Athens, United States
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Introduction: The COVID-19 pandemic posed global health challenges. Understanding SARS-CoV-2’s evolutionary dynamics, especially fitness and immune escape, is vital for public health. This study uses protein language models to assess how genetic variations affect viral adaptability and immunity.Methods: We applied the CoVFit model to predict Fitness and Immune Escape Index (IEI), validated by a null model based on neutral evolution. We analyzed 2,504,278 SARS-CoV-2 spike sequences, including 160,892 variants, tracking evolution from 2020 to May 2024, comparing real and random mutants’ Fitness and IEI.Results: Our analysis revealed an increase in Fitness (mean rising from 0.227 in 2020 to 0.930 in 2024) and IEI (mean increasing from 0.171 to 0.555) for North American samples. Globally, the comparison of Fitness and IEI between real and random mutants (generated by the null model) revealed statistically significant differences (real mutant Fitness 0.3849 vs. random mutant 0.2046, p < 0.001, KS test; real mutant IEI 0.2894 vs. random mutant 0.1895, p < 0.001, KS test), indicating strong selective pressure; the JN.1 lineage dominated (94% of sequences by April 2024), underscoring its evolutionary advantage.Conclusions: CoVFit offers key insights into SARS-CoV-2 evolution, aiding vaccine design. Persistent viral adaptation despite interventions highlights the need for surveillance and adaptive strategies using tools like CoVFit for preparedness.
Keywords: SARS-CoV-2, Spike protein, Protein Language Models, protein fitness, immune escape, retrospective analysis
Received: 13 Feb 2025; Accepted: 30 May 2025.
Copyright: © 2025 Peng, Lyu, Carmola1, Subedi, Mubassir, Bakheet and Bahl. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Sihua Peng, University of Georgia, Athens, United States
Justin Bahl, University of Georgia, Athens, United States
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